Browsing by Author "Pham, T."

Now showing 1 - 4 of 4

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Agilely assigning sensing assets to mission tasks in a coalition context
(IEEE, 2013) Preece, A.; Norman, T.; de Mel, G.; Pizzocaro, D.; Şensoy, Murat; Pham, T.; Computer Science; ŞENSOY, Murat
When managing intelligence, surveillance, and reconnaissance (ISR) operations in a coalition context, assigning available sensing assets to mission tasks can be challenging. The authors' approach to ISR asset assignment uses ontologies, allocation algorithms, and a service-oriented architecture.
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Interest-based negotiation for policy-regulated asset sharing
(Springer Nature, 2016) Parizas, C.; de Mel, G.; Preece, A. D.; Şensoy, Murat; Calo, S. B.; Pham, T.; Computer Science; ŞENSOY, Murat
Resources sharing is an important but complex problem to be solved. The problem is exacerbated in a coalition context due to policy constraints, that reflect concerns regarding security, privacy and performance to name a few, placed on the resources. Thus, to effectively share resources, members of a coalition need to negotiate on policies and at times refine them to meet the needs of the operating environment. Towards achieving this goal, in this work we propose and evaluate a novel policy negotiation mechanism based on the interest-based negotiation paradigm. Interest-based negotiation, promotes collaboration when compared with the traditional, position-based negotiation approaches.
Open Access
Reasoning with uncertain information and trust
(SPIE, 2013) Şensoy, Murat; Mel, G. de; Fokoue, A.; Norman, T. J.; Pan, J. Z.; Tang, Y.; Oren, N.; Sycara, K.; Kaplan, L.; Pham, T.; Computer Science; ŞENSOY, Murat
A limitation of standard Description Logics is its inability to reason with uncertain and vague knowledge. Although probabilistic and fuzzy extensions of DLs exist, which provide an explicit representation of uncertainty, they do not provide an explicit means for reasoning about second order uncertainty. Dempster-Shafer theory of evidence (DST) overcomes this weakness and provides means to fuse and reason about uncertain information. In this paper, we combine DL-Lite with DST to allow scalable reasoning over uncertain semantic knowledge bases. Furthermore, our formalism allows for the detection of conflicts between the fused information and domain constraints. Finally, we propose methods to resolve such conflicts through trust revision by exploiting evidence regarding the information sources. The effectiveness of the proposed approaches is shown through simulations under various settings.
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TRIBE: Trust revision for information based on evidence
(IEEE, 2013) Şensoy, Murat; de Mel, G.; Kaplan, L.; Pham, T.; Norman, T. J.; Computer Science; ŞENSOY, Murat
In recent years, the number of information sources available to support decision-making has increased dramatically. However, more information sources do not always mean higher precision in the fused information. This is partially due to the fact that some of these sources may be erroneous or malicious. Therefore, it is critical to asses the trust in information before performing fusion. To estimate trust in information, existing approaches use trustworthiness of its source as a proxy. We argue that conflicts between information may also serve as evidence to reduce trust in information. In this paper, we use subjective opinions to represent information from diverse sources. We propose to exploit conflicts between opinions to revise their trustworthiness. For this purpose, we formalise trust revision as a constraint optimisation problem. Through extensive empirical studies, we show that our approach significantly outperform existing ones in the face of malicious information sources.